Build big data adaptability through rapid experimentation

1. Build Big Data Adaptability Through Rapid Experimentation Discover why your organization must experiment with high volume, velocity, and variety for its big data strategy to succeed.

2. Summary Adaptable organizations that embrace big data for a competitive advantage double-down on the idea of big data concepts both in content and format. Rapid experimentation is at the core of adaptability, and big data analytics is the best secret to rapid experimentation. At any point in time, your innovation funnel should be flooded with a variety of ideas that are rapidly moving their way to become product, service, or relationship offerings.  It all starts with a mindset, so schedule time today to talk to your team about your objectives and intentions. The music in the marketplace requires a quickstep, so make sure you're doing the right dance.

3. Big data + enterprise The large enterprises comprising a smaller fraction of the landscape are the most aggressive in their big data roll out strategies. These enterprises are looking to understand their customer segment better to increase sales. From analyzing customer influences on preferred telecommunications carriers to personalized customer offers, big data analytics is increasingly playing a vital role. Micro market segmentation and analysis is also playing a key role given the diversity and vastness of the local market.

4. Big data If you're trying to waltz when your customers want to quickstep, they'll choose your competition. This anxiety-inducing situation often points leaders in the direction of big data, which is a smart move. However, most organizations approach big data with too much trepidation -- they're dipping their toes in the water when they should be plunging into the deep end. Adaptable organizations experiment rapidly with their offerings (products, services, and relationships) and build strong discovery capabilities. There's no better way to accelerate discovery than to embrace big data in your strategy -- the key is to attack this with purpose and vigor. To dramatically increase adaptability, you must build an organization that experiments in a big data fashion: with high volume, velocity, and variety.

5. Volume: a wealth of options Big data is classically hallmarked by high volume (exabytes), high velocity (real-time data streams), and high variety (video, audio, and unstructured content), and your approach to experimentation should be no different. To start, you should plan for a high volume of experiments running at any particular point in time. You should focus your experiments on finding the right product (or service)/market combinations; advanced companies are also experimenting with processes, value chains, and strategies (i.e., the strategy of no strategy). You need a high volume of experiments to hedge your bets; there's no way to know what will click, so you always need experiments in your innovation funnel. The best way to do this is to have multiple teams work on different ideas and assign everyone the responsibility for coming up with new ideas. Google is the paragon for innovation; employees are free to spend 20% of their time working on whatever they feel is a good idea. A product manager I know at Apple was assigned hundreds of resources to build whatever he thought would work. The combination of culture (i.e., everyone is generating ideas) and structure (i.e., multiple, parallel teams are working on experimentation) should be enough to generate a wealth of experiments. Now you need to move these experiments through the innovation funnel.

6. Velocity: rapid execution The traditional sales funnel inspired me to come up with the idea of an innovation funnel. You should have a slew of ideas that move through a pipeline to eventually become offerings, similar to the way prospects work through a sales funnel to eventually become customers. The difference between a sales funnel and an innovation funnel is that, with an innovation funnel, you have much more control over how fast ideas turn into products or services. In the spirit of big data, your experimentation process must be extremely fast. If it takes you 18 months to build a product that serves a fickle market, you have a huge problem. To increase the throughput of your experiments, take a formal approach to improving your experimentation process. You should clearly define and communicate your intentions to minimize the time it takes to bring an idea into the marketplace, and then work with your big data analytics team on the key areas that take time with the experimentation process. For instance, on a typical Six Sigma Design of Experiments project, a signification amount of time will be spent on data collection. By installing good tools to integrate your operational systems with your CRM systems, you can dramatically reduce the time it takes to collect data. Although doing a root-cause and improvement exercise takes time, you'll see significant improvements in your innovation cycle time after only a few of these efforts.

7. Variety: the spice of innovation They say variety is the spice of life -- it's also the spice of innovation. If you load your innovation funnel with experiments that all have the same theme and your theme is off, you've just turned a bad situation into a worse situation. You should consider the array of products and services you could offer and the potential markets they could serve, and then make sure you have a good mix at any point in your innovation funnel. Also, don't forget about relationships, which are basically services that are free of charge. If your corporate strategy involves any degree of customer loyalty, you must have relationships at least on par with your product and service considerations. To prevent yourself from going insane, figure out your strategic driving force before you start experimenting; your driving force is the locus of your competitive advantage. For instance, a company with a products-offered driving force builds exceptional products and experiments with markets that could benefit from their products. Alternatively, a company with a market-driven driving force understands a particular market extremely well and experiments with products or services that would benefit their customers. So, even though you want variety in your innovation funnel, you also need the structure of a driving force to make sure you stay true to your mission and vision.

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